Admissibility of Estimators in the One Parameter Exponential Family and in Multivariate Location Problems

Abstract

We are concerned with problems related to admissibility and minimaxity of estimators in the one parameter exponential family, and with classes of estimators which improve upon the best invariant estimator in multivariate location problems (dimensions p > or =3). In connection with admissibility problems we give sufficient conditions for the admissibility of nonlinear estimators (aX + b)/(Cx + d) in estimating an arbitrary function g(theta) with quadratic loss.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1980
Accession Number
ADA093188

Entities

People

  • Dan A. Ralescu

Organizations

  • Indiana University Bloomington

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies
  • Human Systems

DTIC Thesaurus Topics

  • Algorithms
  • Computer Science
  • Convolution
  • Data Science
  • Differential Equations
  • Estimators
  • Fuzzy Sets
  • Information Science
  • Mathematics
  • New York
  • Normal Distribution
  • Probability
  • Random Variables
  • Statistical Algorithms
  • Statistics
  • Two Dimensional
  • Universities

Fields of Study

  • Mathematics

Readers

  • Statistical inference.